NDLI: QSAR Study on the Toxicity of Phenols for Fathead Minnows by Using Support Vector Machine and Neural Networks

Content Provider	IEEE Xplore Digital Library
Author	Xiujun Cui Zhinxin Wang Zhuoyong Zhang Xing Yuan de B. Harrington, P.
Copyright Year	2008
Description	Author affiliation: Sci. Press, Beijing (Zhinxin Wang) \|\| Dept. of Chem. & Biochem., Ohio Univ., Athens, OH (de B. Harrington, P.) \|\| Coll. of Urban & Environ. Sci., Northeast Normal Univ., Changchun (Xing Yuan) \|\| Fac. of Chem., Northeast Normal Univ., Changchun (Xiujun Cui; Zhuoyong Zhang)
Abstract	Support victor machine (SVM) and artificial neural networks (ANNs) including back-propagation network (BPNN) and radial basis function network (RBFNN) were used to investigate toxic effect of phenols on fathead minnows. Molecular connectivity index was used as structural descriptor. The applicability of established BPNNs, RBFNNs and SVM models based on optimized parameters was compared using leave-one-out (LOO) cross-validation method. Results showed that all the models investigated were applicable for the quantitative structure-activity relationship (QSAR) studies and the SVM model is slightly better than others. The correlation coefficients between measured toxicities and predicted values of SVM, BPNN and RBFNN models are 0.959, 0.94, and 0.945, respectively.
Starting Page	134
Ending Page	138
File Size	130988
Page Count	5
File Format	PDF
ISBN	9780769533049
DOI	10.1109/ICNC.2008.931
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Chemical hazards Predictive models Educational institutions Raw materials SVM Support vector machines BPNN Chemistry Phenol RBFNN Neural networks QSAR Radial basis function networks Molecular connectivity index Computer networks Artificial intelligence
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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